{"id":374008,"date":"2025-04-07T08:54:20","date_gmt":"2025-04-07T06:54:20","guid":{"rendered":"https:\/\/climatescience.press\/?p=374008"},"modified":"2025-04-07T08:54:21","modified_gmt":"2025-04-07T06:54:21","slug":"more-evidence-on-vapor-pressure-deficit-cloud-reduction-and-climate-change","status":"publish","type":"post","link":"https:\/\/climatescience.press\/?p=374008","title":{"rendered":"More Evidence on Vapor Pressure Deficit, Cloud Reduction, and Climate Change"},"content":{"rendered":"\n
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Watts Up With That?<\/a><\/p>\n\n\n\n

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By Charles T Blaisdell  PhD ChE<\/strong><\/p>\n\n\n\n

Abstract<\/strong><\/p>\n\n\n\n

In addition to WUWT, more and more web sites are mentioning cloud reduction as a source of climate change but offer no source of the cloud reduction.\u00a0 WUWT was the first to published this author\u2019s theory: Cloud Reduction Global Warming, CRGW,\u00a0(1)<\/a>.\u00a0 A critical part of CRGW theory is the relationship between Vapor Pressure Deficet, VPD, and Cloud Fraction.\u00a0 The relationship is logical: as the atmosphere\u2019s water vapor concentration approaches the due point the probability of cloud formation should increase.<\/p>\n\n\n\n

Previous papers by this author have shown that Vapor Pressure Deficit and cloud fraction are loosely correlated (low R^2).\u00a0 The measurement of cloud fraction seems to be the main uncertainty.\u00a0 This essay will show that downwelling Short Wave, SW, radiation to the earth\u2019s surface along with atmospheric enthalpy, En, correlate to Cloud Fraction, CF, thus increasing confidence in VPD as a predictor of cloud fraction.\u00a0 VPD and En are necessary variables in the Cloud Reduction Global Warming , CRGW, model which models current climate change using Clausius\u2013Clapeyron related equations.<\/p>\n\n\n\n

Slicing the earth\u2019s data reveals the change in atmospheric VPD and En vs latitude correlate to cloud fraction.  The earth\u2019s slices suggestion that lower land cover in a slice may be related to cloud cover in addition to the expected sun angle.<\/p>\n\n\n\n

But,  CO2 and VPD are confounded.  Which one is guilty of climate change?<\/p>\n\n\n\n

Introduction and background<\/strong><\/p>\n\n\n\n

The CRGW theory is simply put as: Less water evaporating from land into the atmosphere results in less clouds (less clouds, more sun).  Previous attempts to extract VPD vs cloud fraction correlation vs month were unsuccessful due to the more powerful inter hemisphere forces.  Annual data does not have the inter hemispherical variability. <\/p>\n\n\n\n

The annual data was sliced into 8 slices by latitude to obtain data of the temperature (Temp), specific humidity (SH), and cloud fraction (from NASA\u2019s Physical Science Laboratory, (4)<\/a> and Climate Explorer, (3)<\/a>).  Temp and SH are the only variables needed to calculate VPD and En.  En is a variable that measures the heat (potential energy) present in the atmospheric air at the altitude the Temp and SH data was taken.  En is the atmosphere\u2019s part of the earth\u2019s energy budget (Changes in En are part of the Earth\u2019s Energy Imbalance, EEI).<\/p>\n\n\n\n

The equations used for calculating VPD and En are:<\/p>\n\n\n\n

Water saturation pressure, Pws, is from Vaisala Oyj (2013), (2)<\/a>:<\/p>\n\n\n\n

Pws = 6.116441*10^((Temp * 7.591386\/(240.7263+Temp)))<\/td>(in hPa)<\/td>Eq 1<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

(Note: the above is not an Arrhenius equation but give similar results.)<\/p>\n\n\n\n

Water vapor, Pw, pressure is from Vaisala Oyj (2013) (2)<\/a>:<\/p>\n\n\n\n

Pw  = SH *1000\/(621.9907+SH)<\/td>(in hPa)<\/td>Eq 2<\/td><\/tr>
VPD = Pws \u2013 Pw<\/td>(in hPa)<\/td>Eq 3<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Enthalpy, En, Vaisala Oyj (2013)  (2)<\/a>:<\/p>\n\n\n\n

En = Temp * (1.006+0.00189*SH)+2.501*SH<\/td>(in  kJ\/kg (da) )<\/td>Eq 4<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

These equations are not in Clausius\u2013Clapeyron format but simplified for more convenient use with water.<\/p>\n\n\n\n

A clarification of the annual data used.\u00a0 The VPD or En data is not derived from one point but is the average of many data point over many months.\u00a0 Thus, a VPD of say 4.0 hPa\u00a0 (which is nowhere near the dew point) is the average of a wide range of points from about 10 to 0 hPa.\u00a0 Only the points near 0 could have clouds.\u00a0 Cloud fraction includes rain clouds, high and low clouds, and partly cloudy.\u00a0 The more data that goes into a temperature or specific humidity annual number the higher the probability of an accurate prediction of cloud fraction.<\/p>\n\n\n\n

New Cloud Fraction data<\/strong><\/p>\n\n\n\n

New Cloud Fraction, CF, data was found at Climate Explorer (3)<\/a> , Figure 1.  The big decrease (from previous) in average cloud fraction is very noticeable.  The decreasing slope is a little less than the old data (downloaded in 2021).  The new CF data has a better R^2 and both old and new data seemed to suggest no decrease in CF after 2003.  The new data shows Mt Pinatubo eruption (1991 to 1994) better than the old data.<\/p>\n\n\n

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Figure 1.\u00a0 New and old Cloud Fraction data.<\/figcaption><\/figure>\n<\/div>\n\n\n

With decreasing CF one would expect that shortwave, SW, radiation to the earth\u2019s surface would be increasing.\u00a0 Likewise, the VPD and the En should be increasing. \u00a0Figure 2 suggests that all three (SW radiation, VPD, and En) do.\u00a0 Figure 2\u2019s 2003 to 2021 data suggest an increasing slope for these three variables when the CF chart suggests a flat response.\u00a0 This observation could be interpreted as a lack of sensitivity to the CF data or there is another source of energy to the atmosphere.\u00a0 Since atmospheric SW radiation can only come from the sun the lack of sensitivity in the CF data is the most probable explanation.\u00a0 If this is true SW radiation to the surface may be a proxy for CF.<\/p>\n\n\n

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Figure 2 comparison of New CF with SW radiation, VPD and En<\/figcaption><\/figure>\n<\/div>\n\n\n

A check on incoming SW radiation variations, Figure 3, suggests that some of the perturbations in the sun\u2019s irradiance line up with the SW radiation perturbations to the surface, but the magnitude of the perturbations is small compared to the overall increase in SW radiation to the surface.\u00a0 Figure 3 uses the same scale difference in SW radiation as the SW to the surface graph (to be accurate the difference use for the solar irradiance should be \u00bc of that shown (to allow for day\/night and the curvature of the earth) making the solar perturbations even less significant.<\/p>\n\n\n\n

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Figure 3.\u00a0 Comparison of CF, SW radiation to surface, and Solar irradiance.<\/figcaption><\/figure>\n\n\n\n

Slicing the Earth<\/strong><\/p>\n\n\n\n

\u00a0The earth was sliced in 20 deg sections shown in Figure 4.\u00a0\u00a0 The expected temperature profile shows a small shift in temperature from the 1970 period to the 2020 period with the maximum change in temperature occurring either side of the angle the sun is hitting, no surprise.<\/p>\n\n\n

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   Figure 5 Cloud profile of the earth<\/figcaption><\/figure>\n<\/div>\n\n\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/p>\n\n\n

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Figure 5 Cloud profile of the earth<\/figcaption><\/figure>\n<\/div>\n\n\n

Figures 6 and 7 investigate Cloud Fraction correlation to VPD and En (using equations above).<\/p>\n\n\n

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Figure 6.\u00a0 VPD vs Cloud Fraction<\/figcaption><\/figure>\n<\/div>\n\n
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Figure 7\u00a0 VPD vs En<\/figcaption><\/figure>\n<\/div>\n\n\n

The CRGW model for predicting climate change relies on a good correlation of VPD to Cloud Fraction and Enthalpy.\u00a0 Figures 6 and 7 show that the looked for correlation is present in the earth\u2019s slice data as well as the correlations used in the model.\u00a0 Figure 6 has an interesting point that does not seem to belong (circled in red) that is the only data point that has no land in it\u2019s slice.\u00a0\u00a0 With that curiosity Figure 8 was plotted showing that the amount of land in a slice correlates to the percent of the temperature change in that slice.\u00a0 This is the expected correlation for the CRGW theory: since the change in ET originates from land it should correlate to land area.<\/p>\n\n\n

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Figure 8\u00a0 Change in temp. vs % Land<\/figcaption><\/figure>\n<\/div>\n\n
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Figure 9 Temp change vs sun angle.<\/figcaption><\/figure>\n<\/div>\n\n\n

Figure 9 shows the expected correlation of sun angle to temperature change.  Note correlation to Land is stronger than to sun angle.<\/p>\n\n\n\n

What about CO2?<\/strong><\/p>\n\n\n\n

To be fair, an attempt was made to plot CO2 data for these graphs, all that was found were NASA pictures.  Interpreting the pictures, it was obvious that for CO2:<\/p>\n\n\n\n